1. Field of the Invention
This invention pertains generally to image compression and decompression, and more particularly to fractal image compression and decompression, and most particularly to obtaining color constancy during the decompression of fractally compressed images.
2. Description of Related Art
Data compression may generally be defined as processes of transforming information from one representation to another, smaller representation from which the original data, or a close approximation thereto, can be recovered by the complementary processes of data decompression. The compression and decompression processes are often referred to as coding and decoding. Techniques for compressing digital image data include MPEG, MJPEG, JPEG, DCT, PNG, wavelet, and fractal.
The storage and transmission of large amounts of data are often facilitated by the use of compression and decompression techniques. In particular, the transmission and storage of visual images involves large amounts of data, and benefits greatly from image compression and decompression techniques. However, when compressed image data is decompressed to output on a display device or printer or other output device, problems can result. One problem is to ensure color constancy among the images produced on different displays or other output devices.
Scene lighting conditions cause two major problems or limitations in color images compared to the direct human observation of the scenes. First, there is a comparative loss of detail and color in shadow zones of images captured by both photographic and electronic cameras. This is the dynamic range problem. Second, changes in the spectral distribution of the illumination source cause color distortions in the images. This is the color constancy problem.
Electronic cameras (e.g., based on CCD detector arrays) can acquire image data across a wide dynamic range. This range is typically wide enough to handle most illumination variations within scenes, and camera adjustments can usually handle illumination variations from scene to scene. However, this range is usually lost when the image is digitized or when the image is output to a printer or display, which has a much more limited dynamic range.
The color constancy problem typically arises from the spectral differences between daylight and artificial lighting. Different film and/or filters can be used to try to compensate, but these do not provide any dynamic range compression, and cause detail and color in the shadows to be lost or severely attenuated compared to what a human observer would actually see.
The development of image processing systems has been at the heart of the recent digital image revolution. These systems process captured digital images to enhance their clarity and details using sophisticated image processing algorithms, resulting in images that are substantially more detailed and accurate than previously. However, a substantial difference remains between an image perceived by a person and an image captured and reproduced on a display. Despite improvements in digital image processing systems, they still cannot reproduce images with the same level of detail, color constancy, and lightness, as a human perceives. This is due in part because the human eye has a greater dynamic range compression than current digital image systems. Dynamic range compression refers to the ability to distinguish varying levels of light. The human eye has a dynamic range compression of about 1000:1, which means that the eye can distinguish about 1000 levels of light variation. By contrast, digital image systems typically use 8 bits/pixel, which allows for a dynamic range compression of only 256:1.
Current technologies for creating, storing, and display of electronic images must be duplicated for the various end displays, due to differences in resolution, dynamic range, and color gamut. This is currently overcome by choosing from a set of images on server equipment, or by resizing the image when displayed. Usually, a completely separate image must be processed to do anything about the dynamic range at all.
The rendering format for a device consists of the height and width of a rendered image, and it's color gamut or “dynamic range”. Different formats are appropriate to different rendering devices, such as a large dynamic range and color gamut for a CRT, a large dynamic range and height and width for an HDTV device, and a very large height and width, but smaller dynamic range and color gamut for printed media.